Back to school

SAS Institute’s roots in academia run deep.

I choose the word “roots” advisedly; the Statistical Analytics System from which we draw our name began as a research project in North Carolina State University’s agriculture program in 1966. The project was joined by a graduate student named James Goodnight in 1967. Dr. Goodnight and three partners established SAS Institute with headquarters across the street from the university in the early 1970s.

While our footprint in Fortune 500 companies grew, education was always an important focus for SAS. The company campus in Cary, N.C., hosts day care facilities and elementary and secondary schools, including the Cary Academy, a prep school focused on technology development. SAS Academic Program offers students, teachers and researchers free access to analytics tools to kick-start their learning.

In some ways, it’s like we never really graduated.

Analytics lies at the heart of the evidence-informed decision-making culture that will drive public sector programming and private sector strategy for the foreseeable future. But the demand for the minds to power that engine of policy and commerce is outstripping supply. McKinsey and Co. has predicted the U.S. will face a shortfall of up to 190,000 people with analytical expertise, and 1.5 million managers and analysts who understand analytics well enough to act as decision-makers, by 2018. Closer to home, the Canadian Big Data Consortium pegs those numbers at 19,000 and 150,000, respectively.

Filling the gap

It’s a need that hasn’t gone unnoticed. “The switch happened five or six years ago,” says Jean-François Plante, Associate Professor with French-language business school HEC Montréal’s Department of Decision Sciences. “It used to be someone would ask, ‘What are you doing?’ Now, someone drops off a business card and says, ‘I want to hire 10 interns.’” With connections to 80 per cent of the post-secondary data science programs in Canada, we at SAS see talent inquiries from industry almost daily.

HEC started offering a program in business intelligence—“analytics wasn’t a common term then,” says Plante—in 2001. Today, the school’s Masters’ level analytics program boasts 50-60 students. “That’s a fair number for a specialty,” Plante says.

HEC is only one of many schools operating in partnership with SAS to bridge the analytics skills gap in Canada. Programs range from the post-secondary to the post-graduate; SAS contributes free or low-cost software and support, along with connections to customers looking to add staff with analytics skills. SAS expertise and thought leadership are also front and centre—for example, our Director of Global Product Marketing, Bernard Blais, spoke to students at a data philanthropy event hosted by IVADO, a Quebec-based data science organization, about the value of using real-life datasets to gain hands-on experience.

Canadian schools have been leaders in partnering with SAS. We’re No. 3 worldwide in the number of downloads of SAS University Edition downloads, with 65,000, and there are more than 50 graduate degree programs in 71 educational institutions in the SAS Academic Program, which reaches more than 8,000 students.

With the advent of a digitally native generation, for whom technology is second nature, new paradigms in teaching and learning are necessary. “Traditional subject-specific and instruction-based learning does not meet the expectations of the industry and, more importantly, does not fit the new generation of student learning styles,” says Sacha Noukhovitch, education and student research expert with the STEM Fellowship, a student-run Canadian non-profit aimed at developing skills in science, technology, engineering and mathematics (STEM). In partnership with SAS and others, the STEM Fellowship sponsors an annual Big Data Challenge to drive interest among high-schoolers in data science.

This year’s competition drew 29 teams. Each is provided datasets, data science tools and educational resources from SAS and the University of Toronto’s SciNet, and tasked with developing a project around the theme “Think Global and Act Local with Big Data,” their reports published in the prestigious STEM Fellowship Journal. The projects are meant to develop:

Computational Thinking: How to turn large amounts of data into a “How might we …?” problem and refine the scope with data-based reasoning;
Design Mindset:  Generating solutions when only part of the requirements are known ahead of time;
Cognitive Load Management:  Filtering usable information from disparate datasets.

First and foremost, though, is developing a sense of global citizenship. This year’s theme pertains to the United Nations’ 17 sustainable development goals, with subjects like the correlation of food and climate change, sustainable infrastructure, renewable energy and the impact of climate change and the economy.

Global perspective

That global perspective is also evident in the 2017 Queen’s University Innovation Challenge, which drew 111 teams from nine countries around the world—not just Canada and the U.S., but England, Portugal, France, Ukraine, Australia, and others—to compete for a share of $40,000 in prizes. The university consulted with the U.N. to develop this year’s theme, which has student teams applying artificial intelligence and machine learning to problems of global food security.

“You want the subject to be wide enough to engage students worldwide,” says Dean McKeown, Associate Director, Administration, with the Scotiabank Centre for Customer Analytics at Queen’s University’s Smith School of Business in Kingston, Ont. The issue is a worldwide one, but manifests itself in different ways in different regions.

“Food security in Somalia is not the same as food security in downtown Toronto,” McKeown says—the struggle of a single mother trying to put food on the table is a different problem than a lack of potable water for crops.

Now in its third year, the challenge focuses on actionable projects. 2016 winners developed a dynamic pricing strategy for berries at Loblaw grocery stores that treated products as competitive, not complementary, and projected a $75 million increase in revenues.

Last year’s winning team, announced Nov. 24, was from Ukrainian Catholic University, Lviv, Ukraine. The team’s project, a drone-based detection system that identifies and projects the spread of a plant fungus to treat crops before the damage is done, relies on advanced artificial intelligence, machine learning and a database of images of fungus-infected plants to pinpoint the spread.

The university is now availing itself of the SAS Viya cloud-based analytics and collaboration platform, opening up higher-end processing for analytics problems. “It really democratizes the process,” McKeown says.

Queen’s has had an academic license from SAS “from time immemorial,” says McKeown. Originally acquired for the university’s Master of Science in Public Health program, that SAS capability now also powers the Master’s of Management Analytics program, launched five years ago. The business school  doesn’t aim to churn out graduates with a primarily technical focus (though SAS certification is encouraged as holding “tremendous value”). The program aspires to create what McKeown calls “the Purple People”—those who can liaise between the red team and the blue team, between the business side and the technical side. This demands a command of data science tools to communicate the significance of the work to business management.

Disparate Backgorunds

Queen’s came to SAS analytics for its public health program. And it’s almost necessary for those Purple People in training to come to analytics from backgrounds in other fields than computer science. While there are many candidates from a statistics background, data science programs see students from a variety of backgrounds.

Plante says HEC candidates have come to the program from academic backgrounds in engineering, accounting, political science, and other fields. (One student came to program with a post-doctoral degree in psychometrics, the science of the objective measurement of psychological traits and conditions.) “There’s really people from all backgrounds,” Plante says.

That will only increase as younger generations twig to the crossover of data science with their chosen line of work, says Noukhovitch. “A significant amount of high school and university students in a range of fields, from finance to biology, have yet to realize the extent to which data-native thinking crosses over their own respective fields,” Noukhovitch says.

One of the significant groups among the intake for analytics programs is that of back-to-schoolers—people with years of experience in a variety of horizontals who see the application of analytics as a value-add, along with a road to professional advancement. Plante estimates about half of incoming students are in industry in fields like human resources, marketing, engineering, and more.

Analytics is fertile ground for academia, as well as for business strategy as we enter a world of Big Data, machine learning, artificial intelligence, and all that future technology holds for business and public service. With involvement in learning programs across the country, from secondary to graduate studies, SAS is connecting with students at all levels to foster their development in the burgeoning world of data science.

About the author:

As Academic Program Lead for SAS Canada Mark works with academics, instructors and students to help them teach, research and learn with analytics. With more than 50 graduate degree programs in 71 educational institutions in the SAS Canada Academic program Mark is passionate about helping them become part of the evidence based data-driven world by employing the most advanced analytics.